Iterative Interpolation for Parameter Estimation of LFM Signal Based on Fractional Fourier Transform

Song, Jun; Wang, Yixiong; Liu, Yunfei

doi:10.1007/s00034-012-9517-8

Cited by 20 publications

(9 citation statements)

References 16 publications

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“…Therefore, the residual term is the decisive point affecting the parameter estimation precision in Equation ( 8 ). Through conventional algorithms such as Newton-type [ 8 ] and interpolation [ 18 ], the residual term can be estimated. However, the first method suffers from a huge computational cost, and the second is only developed for monocomponent signals.…”

Section: Signal Model and Frftmentioning

confidence: 99%

“…Conventional DFrFT utilizes a coarse-fine search strategy to improve the estimation accuracy. The coarse-fine strategy firstly obtains a crude estimation by searching the maximum FrFT coefficient of the received data, and then, the result is refined by modified methods such as Newton-type methods [ 8 ] and interpolation methods [ 10 , 18 ]. However, these methods require numerous extra calculations and make it difficult to handle the OFDM-LFM signals.…”

Section: Introductionmentioning

confidence: 99%

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Iterative High-Accuracy Parameter Estimation of Uncooperative OFDM-LFM Radar Signals Based on FrFT and Fractional Autocorrelation Interpolation

Liu

Zhao

Zhu

et al. 2018

Sensors

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To improve the parameter estimation performance of uncooperative Orthogonal Frequency Division Multi- (OFDM) Linear Frequency Modulation (LFM) radar signals, this paper proposes an iterative high-accuracy method, which is based on Fractional Fourier Transform (FrFT) and Fractional Autocorrelation (FA) interpolation. Two iterative estimators for rotation angle and center frequencies are derived from the analytical formulations of the OFDM-LFM signal. Both estimators are designed by measuring the residual terms between the quasi peak and the real peak in the fractional spectrum, which were obtained from the finite sampling data. Successful elimination of spectral leakage caused by multiple components of the OFDM-LFM signal is also proposed by a sequential removal of the strong coefficient in the fractional spectrum through an iterative process. The method flow is given and its superior performance is demonstrated by the simulation results.

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Section: Signal Model and Frftmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Iterative High-Accuracy Parameter Estimation of Uncooperative OFDM-LFM Radar Signals Based on FrFT and Fractional Autocorrelation Interpolation

Liu

Zhao

Zhu

et al. 2018

Sensors

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“…In [11,12], the detection technique of matched filter receiver (correlation method) was mentioned, but it is difficult and also needs amplitude modulation which is not suitable for underwater channel. The fractional Fourier transform (FrFT) presents best localization performance in a certain FrFT domain, which is useful for the detection and estimation of multicomponent linear frequency modulation (LFM) signals [15] and some improved algorithms based on FrFT are also proposed, such as EEMD-FrFT [16] and STFT [17]; they overcome some disadvantages such as high computation cost for combined chirp signals. In this paper, a method called mixing change rate-FrFT (MCR-FrFT) is proposed to deal with the drawback.…”

Section: Related Workmentioning

confidence: 99%

A TDoA Localization Scheme for Underwater Sensor Networks with Use of Multilinear Chirp Signals

Cheng¹,

Lin²,

Chen³

et al. 2016

Mobile Information Systems

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Due to the multipath, Doppler, and other effects, the node location signals have high probability of access collision in the underwater acoustic sensor networks (UW-ASNs), and therefore, it causes the signal lost and the access block; therefore, it constrains the networks performance. In this paper, we take the multilinear chirp (MLC) signals as the location signal to improve the anticollision ability. In order to increase the detection efficiency of MLC, we propose a fast efficient detection method called mixing change rate-fractional Fourier transform (MCR-FrFT). This method transforms the combined rates of MLC into symmetry triangle rates and then separates the multiuser signals based on the transformed rates by using FrFT. Theoretical derivation and simulation results show that the proposed method can detect the locations signals, estimate the time difference of arrival (TDoA), reduce the multiple access interference, and improve the location performance.

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“…Another method is using curve fitting over the spectral line via moving least square (MLS) [5], but it will produce an additional computation. The direct interpolation algorithm [6] can obtain high accuracy of parameters estimation while doesn't increase the computational complexity, and the iterative interpolation algorithm [7] further reduced the estimation error, but they are effective only to the no windowing signal. However, in fact, the windowed LFM signal also has to be considered [8,9].…”

Section: Introductionmentioning

confidence: 99%

Method for Estimating the Parameters of LFM Radar Signal

Tan

Fan

2017

ITM Web Conf.

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Abstract. In order to obtain reliable estimate of parameters, it is very important to protect the integrality of linear frequency modulation (LFM) signal. Therefore, in the practical LFM radar signal processing, the length of data frame is often greater than the pulse width (PW) of signal. In this condition, estimating the parameters by fractional Fourier transform (FrFT) will cause the signal to noise ratio (SNR) decrease. Aiming at this problem, we multiply the data frame by a Gaussian window to improve the SNR. Besides, for a further improvement of parameters estimation precision, a novel algorithm is derived via Lagrange interpolation polynomial, and we enhance the algorithm by a logarithmic transformation. Simulation results demonstrate that the derived algorithm significantly reduces the estimation errors of chirp-rate and initial frequency.

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Iterative Interpolation for Parameter Estimation of LFM Signal Based on Fractional Fourier Transform

Cited by 20 publications

References 16 publications

Iterative High-Accuracy Parameter Estimation of Uncooperative OFDM-LFM Radar Signals Based on FrFT and Fractional Autocorrelation Interpolation

Iterative High-Accuracy Parameter Estimation of Uncooperative OFDM-LFM Radar Signals Based on FrFT and Fractional Autocorrelation Interpolation

A TDoA Localization Scheme for Underwater Sensor Networks with Use of Multilinear Chirp Signals

Method for Estimating the Parameters of LFM Radar Signal

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